Abstract
Resnet, from its emergence, has always been a state-of-the-art model for facial recognition problems. The 2019 Bench Council posted several challenges, including an International 3D Face Recognition Algorithm Challenge, which aims at soliciting new approaches to advance the state-of-the-art in face recognition. We focus on utilizing a 4-channeled Resnet on this new problem and achieve 90% validation set accuracy resulting in second prize on the Bench-19 International Artificial Intelligence System Challenges.
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Xiong, X. (2020). Utilization of Resnet in RGB-D Facial Recognition Problems. In: Gao, W., Zhan, J., Fox, G., Lu, X., Stanzione, D. (eds) Benchmarking, Measuring, and Optimizing. Bench 2019. Lecture Notes in Computer Science(), vol 12093. Springer, Cham. https://doi.org/10.1007/978-3-030-49556-5_16
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DOI: https://doi.org/10.1007/978-3-030-49556-5_16
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